Improvement of the Ferroelectric Response of La-Doped Hafnium Zirconium Oxide Employing Tungsten Oxide Interfacial Layer with Back-End-of-Line Compatibility.

In this work, the impact of a tungsten oxide (WO3) seed and capping layer for ferroelectric La-doped (Hf, Zr)O2 (La:HZO) based capacitors, designed with back-end-of-line (BEOL) compatibility, is systematically investigated. The WO3 capping layer supplies oxygen to the La:HZO layer throughout the fabrication process and during device cycling. This facilitates the annihilation of oxygen vacancies (Vo) within the La:HZO layer, thereby stabilizing its ferroelectric orthorhombic phase and resulting in an increase of the remanent polarization (Pr) value in the capacitor. Moreover, the effectiveness of the WO3 capping layer depends on the seed layer of the HZO film, suggesting that proper combination of the seed and capping layers should be employed to maximize the ferroelectric response. Finally, a TiN/TiO2 seed layer/La:HZO/WO3 capping layer/TiN capacitor is successfully fabricated and optimized by a complete set of atomic layer deposition (ALD) processes, achieving a superior 2Pr value and endurance value of more than 109 cycles at an electric field of 2.5 MV/cm. The WO3 capping layer is anticipated to offer a viable solution for doped HZO capacitors with reduced thickness, addressing the challenge of elevated Vo levels that favor the tetragonal phase and result in low 2Pr values.

Economic Evaluations of Everolimus Versus Other Hormonal Therapies in the Treatment of HR+/HER2- Advanced Breast Cancer From a US Payer Perspective.

INTRODUCTION: The objective of the study was to assess the cost-effectiveness of EVE+EXE versus endocrine monotherapies in the treatment of postmenopausal women with HR(+), HER2(-) ABC after failure of treatment with nonsteroidal aromatase inhibitors from a US third-party payer perspective. MATERIALS AND METHODS: A Markov model was developed to evaluate the costs and effectiveness associated with EVE+EXE, exemestane (EXE), fulvestrant (FUL), and tamoxifen (TAM) over a 10-year time horizon. The model included 3 health states: responsive/stable disease, progression, or death. Monthly transition probabilities were estimated based on the BOLERO-2 (Breast cancer trials of OraL EveROlimus-2) data and network meta-analyses. Costs included drug acquisition and administration costs, medical costs associated health states, and costs for managing adverse events (AEs). Utilities for each health state and disutilities for AEs were derived from the literature. Incremental costs per quality-adjusted life year (QALY) were estimated by comparing EVE+EXE with each endocrine monotherapy. One-way and probabilistic sensitivity analyses were performed. RESULTS: In the base case, EVE+EXE was associated with 1.99 QALYs and total direct costs of $258,648 over 10 years. The incremental cost per QALY of EVE+EXE was $139,740 compared with EXE, $157,749 compared with FUL, and $115,624 compared with TAM. At a willingness-to-pay threshold of $130,000/QALY or above, EVE+EXE appeared to be the most cost-effective treatment among all drugs. CONCLUSIONS: Everolimus with EXE demonstrated QALY improvements compared with 3 other endocrine monotherapies. Benchmarked by the economic value of other novel cancer therapies, EVE+EXE might be considered a cost-effective option compared with endocrine therapies for HR(+)/HER2(-) ABC.

Assessment of income growth in patients with rheumatoid arthritis treated with anti-tumor necrosis factor therapy.

OBJECTIVES: To compare income growth over time between employees with RA treated with anti-TNFs and those treated with methotrexate (MTX). METHODS: Privately insured employees (aged ≥18) with ≥1 RA diagnosis (ICD-9: 714.0) were identified from a large-scale US employer claims database (1998-2011). Patients were stratified into treatment groups (anti-TNF-treated patients and MTX-monotherapy patients) based on their treatment history. The anti-TNF-treated patients comprised patients who filled ≥1 prescription for anti-TNFs, with or without MTX (index date defined as the date of the first anti-TNF prescription). The MTX-treated patients comprised patients who filled ≥1 prescription for MTX-monotherapy (index date randomly selected). The primary study outcome was the annual income growth rate (US dollars). Patients were followed from their index date to health plan disenrollment or the end of data availability (maximum follow-up of 5 years). The effect of treatment type on income growth was assessed using a multivariable generalized estimating equation model, adjusting for key baseline characteristics. Income growth was compared to that of the general employed population using Social Security data (1998-2011). RESULTS: The regression-adjusted annual growth rate in income for anti-TNF-treated patients (n = 1848) was 2.8% (CI = 1.9-3.6%), significantly greater (p < 0.05) than the 0.6% (CI = -0.2-1.4%) for MTX-monotherapy patients (n = 1866). Compared to the general employed population, income growth was lower (p < 0.05) for MTX-monotherapy patients and comparable for anti-TNF-treated patients. CONCLUSIONS: Compared to MTX-monotherapy, anti-TNF treatment is associated with a higher income growth rate among employees with RA. Anti-TNF-treated patients experienced comparable income growth to the general employed population norm.

Treatment patterns, resource use, and economic outcomes associated with atypical antipsychotic prescriptions in children and adolescents with attention-deficit hyperactivity disorder in quebec.

OBJECTIVE: To assess treatment patterns, health care resource utilization (HRU), and costs among previously stimulant-treated children and adolescents with attention-deficit hyperactivity disorder (ADHD) receiving atypical antipsychotic (AAP) prescriptions in Quebec. METHODS: Health care claims data extracted from Quebec's provincial health plan database between March 2007 and February 2012 were analyzed. Children and adolescents (6 to 17 years) with ADHD who were taking a stimulant and either switched to, or augmented with, an AAP (with the first AAP defined as the index AAP) without a documented diagnosis for which AAPs are Health Canada-approved were included. Discontinuation, augmentation, and switching of the index AAP during the 12-month, follow-up period were estimated using Kaplan-Meier survival analysis. HRU and costs for the 6 months before (baseline period) and after initiation of the index AAP were compared. RESULTS: A total of 453 children and adolescents with ADHD, mostly male (74.6%) and aged 6 to 12 years (73.7%), met the inclusion criteria. The 12-month discontinuation, augmentation, and switching rates were 45.5%, 68.2%, and 80.7%, respectively. Patients had, on average, more all-cause prescription fills (22.2, compared with 13.3) and incurred more all-cause pharmacy ($889, compared with $710), total medical ($1096, compared with $644), and total health care ($1985, compared with $1354) costs during the 6-month study period than during the 6-month baseline period (all P < 0.05). Similarly, ADHD-related total health care costs were higher during the study period ($1269, compared with $835; P < 0.05); all-cause and ADHD-related total health care costs increased by 46.6% and 52.0%, respectively. CONCLUSION: Use of an AAP among stimulant-treated children and adolescents with ADHD in Quebec was associated with high rates of therapy changes and increased HRU and costs.

Development and validation of a claims-based prediction model for COPD severity.

BACKGROUND: Administrative claims are an important data source for COPD research but lack a validated measure of patient COPD severity, which is an important determinant of treatment and outcomes. METHODS: Patients with ≥1 diagnosis of COPD and spirometry results from 01/2004-05/2011 were identified from an electronic health records database linked to healthcare claims. Patients were classified into 3 COPD severity groups based on spirometry and Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines: GOLD-Unclassified, Mild/Moderate, and Severe/Very Severe. A multinomial logistic regression model was constructed using claims data from 3 months before and after (observation period) the most recent spirometry (index date) to categorize patient COPD severity. A random selection of 90% of patients in each severity level was selected to build the model, and the remaining 10% were used as a validation sample. Model predictions were evaluated for sensitivity, specificity, accuracy, and concordance. RESULTS: Among 2028 COPD patients who met sample selection criteria, 886, 683, and 459 patients were in the GOLD-Unclassified, Mild/Moderate, and Severe/Very Severe categories, respectively. The final model included age, sex, comorbidities (such as pulmonary fibrosis and diabetes), COPD-related resource utilization (such as oxygen use), and all-cause healthcare utilization. In the validation sample, the model correctly predicted COPD severity for 62.7% of all patients (accuracy for predicting GOLD-Unclassified: 73.5%; Mild/Moderate: 70.6%; Severe/Very Severe: 81.4%) with kappa = 0.41. CONCLUSIONS: The prediction model was developed using clinically measured COPD severity to provide researchers an approach to classify patients using claims data when clinical measures are not available.

Rare variant analysis for family-based design.

Genome-wide association studies have been able to identify disease associations with many common variants; however most of the estimated genetic contribution explained by these variants appears to be very modest. Rare variants are thought to have larger effect sizes compared to common SNPs but effects of rare variants cannot be tested in the GWAS setting. Here we propose a novel method to test for association of rare variants obtained by sequencing in family-based samples by collapsing the standard family-based association test (FBAT) statistic over a region of interest. We also propose a suitable weighting scheme so that low frequency SNPs that may be enriched in functional variants can be upweighted compared to common variants. Using simulations we show that the family-based methods perform at par with the population-based methods under no population stratification. By construction, family-based tests are completely robust to population stratification; we show that our proposed methods remain valid even when population stratification is present.

Budget impact analysis of everolimus for the treatment of hormone receptor positive, human epidermal growth factor receptor-2 negative (HER2-) advanced breast cancer in the United States.

OBJECTIVE: To estimate the budget impact of everolimus as the first and second treatment option after letrozole or anastrozole (L/A) failure for post-menopausal women with hormone receptor positive (HR+), human epidermal growth factor receptor-2 negative (HER2-) advanced breast cancer (ABC). METHODS: Pharmacy and medical budget impacts (2011 USD) were estimated over the first year of everolimus use in HR+, HER2- ABC from a US payer perspective. Epidemiology data were used to estimate target population size. Pre-everolimus entry treatment options included exemestane, fulvestrant, and tamoxifen. Pre- and post-everolimus entry market shares were estimated based on market research and assumptions. Drug costs were based on wholesale acquisition cost. Patients were assumed to be on treatment until progression or death. Annual medical costs were calculated as the average of pre- and post-progression medical costs weighted by the time in each period, adjusted for survival. One-way and two-way sensitivity analyses were conducted to assess the model robustness. RESULTS: In a hypothetical 1,000,000 member plan, 72 and 159 patients were expected to be candidates for everolimus treatment as first and second treatment option, respectively, after L/A failure. The total budget impact for the first year post-everolimus entry was $0.044 per member per month [PMPM] (pharmacy budget: $0.058 PMPM; medical budget: -$0.014 PMPM), assuming 10% of the target population would receive everolimus. The total budget impacts for the first and second treatment options after L/A failure were $0.014 PMPM (pharmacy budget: $0.018; medical budget: -$0.004) and $0.030 PMPM (pharmacy budget: $0.040; medical budget: -$0.010), respectively. Results remained robust in sensitivity analyses. LIMITATIONS: Assumptions about some model input parameters were necessary and may impact results. CONCLUSIONS: Increased pharmacy costs for HR+, HER2- ABC following everolimus entry are expected to be partially offset by reduced medical service costs. Pharmacy and total budget increases were modest.

Association of genetic loci with sleep apnea in European Americans and African-Americans: the Candidate Gene Association Resource (CARe).

Although obstructive sleep apnea (OSA) is known to have a strong familial basis, no genetic polymorphisms influencing apnea risk have been identified in cross-cohort analyses. We utilized the National Heart, Lung, and Blood Institute (NHLBI) Candidate Gene Association Resource (CARe) to identify sleep apnea susceptibility loci. Using a panel of 46,449 polymorphisms from roughly 2,100 candidate genes on a customized Illumina iSelect chip, we tested for association with the apnea hypopnea index (AHI) as well as moderate to severe OSA (AHI≥15) in 3,551 participants of the Cleveland Family Study and two cohorts participating in the Sleep Heart Health Study.Among 647 African-Americans, rs11126184 in the pleckstrin (PLEK) gene was associated with OSA while rs7030789 in the lysophosphatidic acid receptor 1 (LPAR1) gene was associated with AHI using a chip-wide significance threshold of p-value<2×10(-6). Among 2,904 individuals of European ancestry, rs1409986 in the prostaglandin E2 receptor (PTGER3) gene was significantly associated with OSA. Consistency of effects between rs7030789 and rs1409986 in LPAR1 and PTGER3 and apnea phenotypes were observed in independent clinic-based cohorts.Novel genetic loci for apnea phenotypes were identified through the use of customized gene chips and meta-analyses of cohort data with replication in clinic-based samples. The identified SNPs all lie in genes associated with inflammation suggesting inflammation may play a role in OSA pathogenesis.

Identifying causal rare variants of disease through family-based analysis of Genetics Analysis Workshop 17 data set.

Linkage- and association-based methods have been proposed for mapping disease-causing rare variants. Based on the family information provided in the Genetic Analysis Workshop 17 data set, we formulate a two-pronged approach that combines both methods. Using the identity-by-descent information provided for eight extended pedigrees (n = 697) and the simulated quantitative trait Q1, we explore various traditional nonparametric linkage analysis methods; the best result is obtained by assuming between-family heterogeneity and applying the Haseman-Elston regression to each pedigree separately. We discover strong signals from two genes in two different families and weaker signals for a third gene from two other families. As an exploratory approach, we apply an association test based on a modified family-based association test statistic to all rare variants (frequency < 1% or < 3%) designated as causal for Q1. Family-based association tests correctly identified causal single-nucleotide polymorphisms for four genes (KDR, VEGFA, VEGFC, and FLT1). Our results suggest that both linkage and association tests with families show promise for identifying rare variants.

Association analysis of population-based quantitative trait data: an assessment of ANOVA.

The classical analysis of variance (ANOVA) compares the means of different groups under the assumption that the variances within each of the groups are equal. However, for genetic studies of complex disorders, it is not reasonable to assume that variance of a quantitative trait within each genotype at the trait locus will be equal. Thus, the use of ANOVA may lead to misleading association inferences. In this article, we perform a simulation-based study to assess the rate of false positives and the power of ANOVA under various probability distributions of the quantitative trait and different genetic parameters such as allele frequencies and coefficient of linkage disequilibrium.

A nonparametric regression-based linkage scan of rheumatoid factor-IgM using sib-pair squared sums and differences.

Parametric linkage methods for quantitative trait locus mapping require explicit specification of the probability model of the quantitative trait and hence can lead to misleading linkage inferences when the model assumptions are not valid. Ghosh and Majumder developed a nonparametric regression method based on kernel-smoothing for linkage mapping of quantitative trait locus using squared differences in trait values of independent sib pairs, which is relatively more robust than parametric methods with respect to violations in distributional assumptions. In this study, we modify the above mentioned nonparametric regression method by considering local linear polynomials instead of the Nadaraya-Watson estimator and squared sums of sib-pair trait values in addition to squared differences to perform a genome-wide scan of rheumatoid factor-IgM levels on sib pairs in the Genetic Analysis Workshop 15 simulated data set. We obtain significant evidence of linkage very close to the quantitative trait locus controlling for RF-IgM. We find that the simultaneous use of squared differences and squared sums increases the power to detect linkage compared to using only squared differences. However, because of all the sib pairs are selected for rheumatoid arthritis, there is reduced variance of RF-IgM values, and empirical power to detect linkage is not very high. We also compare the performance of our method with two linear regression approaches: the classical Haseman-Elston method using squared sib-pair trait differences and its extension proposed by Elston et al. using mean-corrected sib-pair cross-products. We find that the proposed nonparametric method yields more power than the linear regression approaches.